| > In 2009 (ish) computer vision was a joke that could recognize very few objects a small percent of the time. Based on only simple color and texture, and sometimes basic shapes. This is completely inaccurate and totally ignores the history of machine vision. Computer vision was in no way a "joke" in 2009. OCR and manufacturing inspection systems have been successfully deployed since the 1980s. Neural networks were being applied to computer vision in autonomous vehicles in 1989: https://www.youtube.com/watch?v=ilP4aPDTBPE > We already have super-human visual cortexes. No we don't: http://rocknrollnerd.github.io/ml/2015/05/27/leopard-sofa.ht... (see also the HN discussion: https://news.ycombinator.com/item?id=9749660) I remember reading about a similar thing that happened in the 1980s to some DARPA funded project that was trying to apply neural networks to tank/vehicle detection: the network got really good at recognizing the foliage that the training images had in them. Robust scene understanding is a very hard problem and still far from solved. Again, research on this has been going on since the 1960s. > But that's no concern, AI advances on from first principles. AI researchers invent better and better algorithms every day, without having a clue what neuroscientists are up to. Do you realize what the 'neural' in neural networks refers to? People working on AI did not suddenly stop paying attention to neuroscience after Perceptrons were invented. |